When it comes to analytics, things can get complicated quickly. In a world of big data and machine learning, most businesses have more data than they know what to do with. Some analytics software packages are so advanced it takes a specialized certification to use them. Delivering real-time insights across the customer journey, at each interaction and across every channel, is the north star of today’s most sophisticated business intelligence (BI) environments.
But achieving these goals is expensive and takes considerable time. Both “business intelligence” and “business analytics” offer the ability to capture and act on information relevant to a customer, product or business. Business analytics develops new insights into performance based on data patterns and statistical methods, while business intelligence uses strategies and technologies to apply data patterns in decision making. When you stay true to foundational BI and analytics principles, you’re automatically set up for success – even without the world’s most advanced tech stack.
Here are three tips for applying analytics and BI you can use today, no matter your budget or analytical prowess.
Tip #1: Uncover the Why
Customer service predictions for 2021 highlight the role of empathy in customer support to improve retention. With the rise of artificial intelligence and self-learning algorithms, it’s not uncommon to lose sight of the fact that customers are people. Within a typical customer conversation with an agent exists a vast amount of data about your business, both good and bad. Listening to everything a customer says, not just information relevant to a support contact, will make the next-best decision that much richer. Are you only listening for what drove this interaction? Or are you hearing everything the customer is saying, including ideas for new product enhancements and feature innovations?
Most companies spend a lot of time looking at what happened and when it happened, but not enough time asking why it happened. One of the richest sources of insight into this type of root-cause intelligence is customer feedback. The question is how do you get to it? One simple way is to use verbatim analysis on customer comments. For example, by categorizing what customers tell our agents into distinct buckets aligned to the business we’re able to pinpoint immediately whether product, process or people are causing an issue. And as soon as we know that we’re prepared to take action.
#2: Collect the Right Data
One of the biggest challenges to successful analytics and BI is getting the right data inputs for meaningful analysis. We see a lot of companies build a front-end CRM system that captures some data, but not everything. For this reason, we spend a lot of time analyzing and re-working data feeds so everything is captured properly before launch. We’ve learned that it’s easy to build great-looking Excel reports, but it’s much harder to capture the right information to begin with. Most business have learned that bad data can lead to bad decisions.
A best-practice approach is to find a support partner with knowledge of your industry that can make recommendations on which data points you need to drive the business. The partner should employ agents with critical-thinking skills who are empowered to make in-the-moment decisions on which questions to ask, information to capture and data to input in the CRM. We’ve used this approach to proactively answer customer questions before they reach an agent. For example, for one client we used information from product engineering about an upcoming outage to add a detailed update in the upfront IVR that included expected timing for a fix. Not only did this allow customers to go back to what they were doing, support also avoided handling unnecessary call volume.
#3: Make Reports Work for You
No single company’s information needs are identical to another’s. Each business model and executive team consumes information in unique ways. This is why it’s important to create a BI and analytics environment that systematically uncovers customer pain points and enables quick action to resolve them. This is especially true in high-growth markets and businesses new to outsourcing. Spending a lot of resources designing attractive reports that no one uses, or complex tables that can’t be interpreted will get you no closer to improving the customer experience than if they didn’t exist.
While some companies spend a lot of time using data-driven intelligence to manage their customer service function, it’s important to spend just as much time identifying things that can help the business as a whole. An optimized customer support environment provides more than efficiency SLAs and productivity metrics. It also captures customer perceptions across channels and in their own words. Data should be reported in ways meaningful to each business line, so leaders have a view into service interactions and the impact through the customer journey. Intelligence about what happened upstream from the customer contact allows a company to plan for new product, game, release or app in a way that prevents future customer issues.
In Summary
Customer support is in a unique position because it sits between the company and its customers. Business intelligence puts data into action by taking information directly from the customer and using insights to improve business performance. In the past, operational leaders relied on instinct and guesswork to figure out the best thing to do for customers. Analytics takes this uncertainty out of the equation. And if you’re in a growth industry, now’s the time to ensure your BI and analytics approach is in place. Stronger customer insights enhance profitability by driving better strategic decisions, faster product enhancements and more dynamic promotional campaigns.
